With the advance of modern science and computer technology, the information exchange between human beings and computers is becoming more important. Traditional way of such communication is via a keyboard for input, and via a display or printer for output. When inputting Chinese characters, one needs to remember the coding scheme, which is very inconvenient. If a computer can have the ability of communicating through speech like human beings, then a dialog based on voice would be possible. This will change the man-machine communication fundamentally, and the overall efficiency of information processing will be greatly increased, Presently, with the great efforts of computer scientists, different types of speech recognition systems, and in particular, Chinese speech recognition systems, have been developed.
Since a Chinese character generally has several homonyms and near homonyms, existing Chinese speech recognition system rely on word, phrase, and higher language level information to resolve the ambiguities in Chinese characters. One generally uses an acoustic model to determine what is the most likely character according to the inputted syllable, and also uses the dictionary with probabilities and the language model where stores the higher level pattern of language usage to resolve the ambiguity of Chinese characters.
However, the recognition of single or un-correlated Chinese character out of context is very difficult, and typically it may be recognized as any one of a set of characters with same or similar pronunciations. As a result, speech input becomes very unreliable when the input is devoid of high level language information, e.g. people's names or city names. In addition, when there are mis-recognized characters in the output of a state-of-the-art speech recognition system, it is desirable to correct them via voice input.
In summary, an intelligent input method for recognizing single or un-correlated Chinese characters in a Chinese speech recognition system is needed.